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Llavero-Valero M, Escalada-San Martín J, Martínez-González MA, Basterra-Gortari FJ, Gea A, Bes-Rastrollo M. Physical Activity Intensity and Type 2 Diabetes: Isotemporal Substitution Models in the "Seguimiento Universidad de Navarra" (SUN) Cohort. J Clin Med 2021; 10:jcm10132744. [PMID: 34206360 PMCID: PMC8267904 DOI: 10.3390/jcm10132744] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Revised: 06/07/2021] [Accepted: 06/17/2021] [Indexed: 11/24/2022] Open
Abstract
Which intensity of physical activity (PA) is associated with type 2 diabetes (T2D) prevention remains unclear. Isotemporal substitution models assess the relationship of replacing the amount of time spent in one activity for another. We aimed to assess T2D incidence associated with light-to-moderate physical activity (LMPA) and vigorous physical activity (VPA) using isotemporal substitution models of one hour (1 h) sitting by 1 h of LMPA or VPA. Furthermore, we evaluated the effect on T2D of an isotemporal substitution of 1 h sitting by 1 h of slow (light physical activity) or brisk–very brisk walking (moderate physical activity). In total, 20,060 participants (both sexes) of the SUN cohort (Spain) initially free of T2D followed-up during a median of 12 years were included. Cox regression models were fitted to assess the association between the substitution of 1 h LMPA, VPA, slow and brisk–very brisk pace by 1 h sitting and T2D. The replacement of 1 h sitting time by 1 h of VPA was associated with an adjusted HR of 0.52 (95% CI: 0.34–0.80), not observed for the substitution by 1 h of LMPA (HR 0.93; 95% CI: 0.73–1.20). An apparent inverse association was observed for the replacement of 1 h sitting time by 1 h of brisk/very brisk walking (HR: 0.69; 95% CI: 0.46–1.04), not observed by 1 h of slow pace. From equal conditions of duration and frequency of PA, the higher the intensity of PA, the greater the T2D prevention.
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Affiliation(s)
- María Llavero-Valero
- Department of Preventive Medicine and Public Health, University of Navarra, 31008 Pamplona, Spain; (M.L.-V.); (M.A.M.-G.); (F.J.B.-G.); (A.G.)
- Department of Endocrinology and Nutrition, University of Navarra, 31008 Pamplona, Spain;
| | - Javier Escalada-San Martín
- Department of Endocrinology and Nutrition, University of Navarra, 31008 Pamplona, Spain;
- Biomedical Research Networking Center for Physiopathology of Obesity and Nutrition (CIBEROBN), Institute of Health Carlos III, 28029 Madrid, Spain
- IDISNA, Navarra Institute for Health Research, 31008 Pamplona, Spain
| | - Miguel A. Martínez-González
- Department of Preventive Medicine and Public Health, University of Navarra, 31008 Pamplona, Spain; (M.L.-V.); (M.A.M.-G.); (F.J.B.-G.); (A.G.)
- Biomedical Research Networking Center for Physiopathology of Obesity and Nutrition (CIBEROBN), Institute of Health Carlos III, 28029 Madrid, Spain
- IDISNA, Navarra Institute for Health Research, 31008 Pamplona, Spain
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Francisco Javier Basterra-Gortari
- Department of Preventive Medicine and Public Health, University of Navarra, 31008 Pamplona, Spain; (M.L.-V.); (M.A.M.-G.); (F.J.B.-G.); (A.G.)
- IDISNA, Navarra Institute for Health Research, 31008 Pamplona, Spain
- Department of Endocrinology and Nutrition, Complejo Hospitalario de Navarra, 31008 Pamplona, Spain
| | - Alfredo Gea
- Department of Preventive Medicine and Public Health, University of Navarra, 31008 Pamplona, Spain; (M.L.-V.); (M.A.M.-G.); (F.J.B.-G.); (A.G.)
- Biomedical Research Networking Center for Physiopathology of Obesity and Nutrition (CIBEROBN), Institute of Health Carlos III, 28029 Madrid, Spain
| | - Maira Bes-Rastrollo
- Department of Preventive Medicine and Public Health, University of Navarra, 31008 Pamplona, Spain; (M.L.-V.); (M.A.M.-G.); (F.J.B.-G.); (A.G.)
- Biomedical Research Networking Center for Physiopathology of Obesity and Nutrition (CIBEROBN), Institute of Health Carlos III, 28029 Madrid, Spain
- IDISNA, Navarra Institute for Health Research, 31008 Pamplona, Spain
- Correspondence: ; Tel.: +34-948-425-600
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An KH, Han KA, Sohn TS, Park IB, Kim HJ, Moon SD, Min KW. Body Fat Is Related to Sedentary Behavior and Light Physical Activity but Not to Moderate-Vigorous Physical Activity in Type 2 Diabetes Mellitus. Diabetes Metab J 2020; 44:316-325. [PMID: 31769237 PMCID: PMC7188971 DOI: 10.4093/dmj.2019.0029] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2019] [Accepted: 04/23/2019] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Sedentary behavior (SB) has emerged as a new risk factor for cardiovascular accidents. We investigated whether physical activity levels or SB were related to percent body fat (%BF) in type 2 diabetes mellitus (T2DM). METHODS In this cross sectional study, we measured the duration of SB, light physical activity (LPA), moderate to vigorous physical activity (MVPA), total energy expenditure, and step counts using a wireless activity tracker (Fitbit HR; FB) for 7 days in free-living conditions, along with %BF using a bio impedance analyzer (Inbody; Biospace) in 120 smartphone users with T2DM. Subjects were divided into exercise (Exe, n=68) and non-exercise (nonExe, n=52) groups based on self-reports of whether the recommended exercises (30 min/day, 3 days/week for 3 months) were performed. SBt, LPAt, MVPAt were transformed from SB, LPA, MVPA for normally distributed variables. RESULTS Participants were: female, 59.2%; age, 59.3±8.4 years; body mass index, 25.5±3.4 kg/m²; glycosylated hemoglobin (HbA1c), 7.6%±1.2%; %BF, 30.4%±7.1%. They performed SB for 15.7±3.7 hr/day, LPA for 4.4±1.7 hr/day, and MVPA for 0.9±0.8 hr/day. The %BF was related to SBt and LPAt, but not to MVPA after adjustments for age, gender, and HbA1c. VPA was significantly higher in the Exe group than in the nonExe group, but SB, LPA, and moderate physical activity were not different. Predicted %BF was 89.494 to 0.105 (age), -13.047 (gender), -0.507 (HbA1c), -7.655 (LPAt) (F[4, 64]=62.929, P<0.001), with an R² of 0.785 in multiple linear regression analysis. CONCLUSION Reduced body fat in elderly diabetic patients might be associated with reduced inactivity and increased LPA.
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Affiliation(s)
- Keun Hee An
- Department of Sports Science, Daejin University, Pocheon, Korea
| | - Kyung Ah Han
- Department of Internal Medicine, Eulji University School of Medicine, Daejeon, Korea
| | - Tae Seo Sohn
- Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Ie Byung Park
- Department of Endocrinology of Metabolism, Gachon University College of Medicine, Incheon, Korea
| | - Hae Jin Kim
- Department of Endocrinology and Metabolism, Ajou University School of Medicine, Suwon, Korea
| | - Sung Dae Moon
- Division of Endocrinology and Metabolism, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Kyung Wan Min
- Department of Internal Medicine, Eulji University School of Medicine, Daejeon, Korea.
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Clustering of Physical Activity and Sedentary Behavior Associated to Risk for Metabolic Syndrome in Older Adults. J Aging Phys Act 2019; 27:781-786. [PMID: 30859890 DOI: 10.1123/japa.2018-0300] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
This study aimed to investigate the clustering patterns of physical activity, sedentary time (ST), and breaks in ST, and the association between the identified clusters at risk for metabolic syndrome associated with obesity in older adults. Participants included 212 users of community health centers in Brazil. A questionnaire about sociodemographic characteristics was used to describe the sample, and physical activity, ST, and breaks in ST were evaluated using accelerometers. Waist circumference was measured as an indicator of the risk for metabolic syndrome. A two-step cluster analysis and logistic regression analysis were conducted. The following four clusters were identified: sitters (37.7%), inactive (28.3%), active (25.5%), and all-day sitters/lightly active (8.5%). Participants in the active cluster were 60% less likely to be at risk for metabolic syndrome. This study may contribute to a comprehensive understanding of which older adult groups need more attention in the context of community health centers.
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Exel J, Mateus N, Travassos B, Gonçalves B, Gomes I, Leite N, Sampaio J. Off-Training Levels of Physical Activity and Sedentary Behavior in Young Athletes: Preliminary Results during a Typical Week. Sports (Basel) 2018; 6:sports6040141. [PMID: 30404165 PMCID: PMC6316694 DOI: 10.3390/sports6040141] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2018] [Revised: 10/30/2018] [Accepted: 11/02/2018] [Indexed: 11/16/2022] Open
Abstract
The level of physical activity (PA) and sedentary behavior (SED) off-training of young athletes may reveal the quality of recovery from training and highlight health related issues. Thus, the aim was to identify and describe young athletes' PA and SED off-training, according to daily life activities. Eight athletes (15.7 ± 2 years, 1.72 ± 0.6 m height, 62.9 ± 10.2 kg) of a sport talent program wore on their waist a tri-axial accelerometer (ActiGraph® wGT9X-link, Shalimar, FL, USA) at 30 Hz for 15 consecutive days, and reported their schedule. A two-step cluster analysis classified three groups according to sedentary PA and MVPA. The Sedentary (56.9%), presented the highest sedentary PA (mean [CI], 37.37 [36.45⁻38.29] min/hour); The Hazardous (19.4%) had the lowest values of sedentary and MVPA (10.07 [9.41⁻10.36] min/hour and 8.67 [7.64⁻9.70] min/hour, respectively). Balanced (23.7%) had the highest MVPA (28.61 [27.16⁻30.07] min/hour). Sedentary had the lowest count of home time associated (20%) and higher school (26%) time when compared to the Hazardous (13%). The Balanced showed the highest count of school (61%) and home time (47%). Different profiles for young athletes revealed alarming behavior in the associations with sedentary PA, sitting and SED breaks, which may influence performance and health.
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Affiliation(s)
- Juliana Exel
- Research Centre in Sports Sciences, Health Sciences and Human Development, CIDESD, CreativeLab Research Community, University of Trás-os-Montes e Alto Douro, UTAD, Quinta de Prados, 5001-801 Vila Real, Portugal.
| | - Nuno Mateus
- Research Centre in Sports Sciences, Health Sciences and Human Development, CIDESD, CreativeLab Research Community, University of Trás-os-Montes e Alto Douro, UTAD, Quinta de Prados, 5001-801 Vila Real, Portugal.
| | - Bruno Travassos
- Research Center in Sports Sciences, Health Sciences and Human Development, CIDESD, Sport Sciences Department, University of Beira Interior, 6201-001 Covilhã, Portugal.
| | - Bruno Gonçalves
- Research Centre in Sports Sciences, Health Sciences and Human Development, CIDESD, CreativeLab Research Community, University of Trás-os-Montes e Alto Douro, UTAD, Quinta de Prados, 5001-801 Vila Real, Portugal.
| | - Isabel Gomes
- Research Centre in Sports Sciences, Health Sciences and Human Development, CIDESD, CreativeLab Research Community, University of Trás-os-Montes e Alto Douro, UTAD, Quinta de Prados, 5001-801 Vila Real, Portugal.
| | - Nuno Leite
- Research Centre in Sports Sciences, Health Sciences and Human Development, CIDESD, CreativeLab Research Community, University of Trás-os-Montes e Alto Douro, UTAD, Quinta de Prados, 5001-801 Vila Real, Portugal.
| | - Jaime Sampaio
- Research Centre in Sports Sciences, Health Sciences and Human Development, CIDESD, CreativeLab Research Community, University of Trás-os-Montes e Alto Douro, UTAD, Quinta de Prados, 5001-801 Vila Real, Portugal.
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Lederman O, Rosenbaum S, Maloney C, Curtis J, Ward PB. Modifiable cardiometabolic risk factors in youth with at-risk mental states: A cross-sectional pilot study. Psychiatry Res 2017; 257:424-430. [PMID: 28837931 DOI: 10.1016/j.psychres.2017.08.034] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/05/2017] [Revised: 08/04/2017] [Accepted: 08/15/2017] [Indexed: 11/29/2022]
Abstract
Young people experiencing psychotic illness engage in low amounts of physical activity have poor fitness levels and poor sleep quality. This study aimed to determine the prevalence of these modifiable cardiometabolic risk factors among individuals with at-risk mental states (ARMS), who are at increased risk of developing psychosis. A cross-sectional study was conducted in a community-based youth mental health service. Thirty participants (23%♀, 21.3 ± 1.7 years old) were recruited, 10 with ARMS, 10 with first-episode psychosis (FEP) and 10 healthy volunteers. Physical activity levels were assessed using self-report and objective measures. Aerobic capacity, upper body strength, hamstring flexibility, forearm grip strength and core endurance were assessed. Sleep quality, depression and anxiety were measured by self-report questionnaire. The ARMS group did not differ significantly on anthropometric measures from FEP or healthy volunteers. They engaged in significantly less physical activity (p < 0.05) and had poorer sleep quality (p < 0.05) than healthy volunteers. Our results are consistent with other studies that found that youth with ARMS are at greater cardiometabolic risk. Interventions aimed at improving these modifiable risk factors may assist with preventing the decline in physical health associated with the development of psychiatric illness.
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Affiliation(s)
- Oscar Lederman
- School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia; Keeping the Body in Mind Program, South Eastern Sydney Local Health District, Sydney, NSW, Australia.
| | - Simon Rosenbaum
- School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia; School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
| | - Chris Maloney
- School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia
| | - Jackie Curtis
- School of Psychiatry, University of New South Wales, Sydney, NSW, Australia; Keeping the Body in Mind Program, South Eastern Sydney Local Health District, Sydney, NSW, Australia
| | - Philip B Ward
- School of Psychiatry, University of New South Wales, Sydney, NSW, Australia; Schizophrenia Research Unit, South Western Sydney Local Health District & Ingham Institute of Applied Medical Research, Liverpool, NSW, Australia
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Stansfield B, Rowlands A, John D, Chastin S, Edwardson C, Hagströmer M. 4th International Conference on Ambulatory Monitoring of Physical Activity and Movement (Limerick, Ireland, 10-12 June 2015). Physiol Meas 2016; 37:E24-E26. [PMID: 27654670 DOI: 10.1088/0967-3334/37/10/e24] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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